Abstract

Since the development of the TRISS (Revised Trauma Score and Injury Severity Score) trauma scoring model several alternative models have been developed. Trauma scoring systems can be broadly categorized into anatomically based injury severity models, e.g. NISS (New Injury Severity Score) and ASCOT (A Severity Characterization of Trauma) or data driven models, e.g. ICISS (Insternational Classification of Diseases Injury Severity Score). Trauma scoring models using death/survival as the outcome measure can either be developed using logistic regression or a neural network approach. Assessment of the worth of a model is most commonly performed using receiver operating curve analysis or the Hosmer-Lemeshow statistic. Both of these statistical methods have their inherent weaknesses when applied to trauma scoring model development. This article aims to review four trauma scoring models and to discuss the limitations of the statistical methods used to assess the worth of these models.

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